One theory behind the worsening software stock decline

The Software Sector Faces a Major Reassessment

The software sector has experienced a significant downturn this week, driven by investor concerns over the potential impact of new automation tools on traditional software licensing models. This shift in sentiment has led to widespread panic selling, with major players like Salesforce and ServiceNow seeing notable declines in their stock prices.

Market Volatility and Investor Concerns

As of Tuesday, the broader software market is showing signs of distress. Shares of industry leaders such as Salesforce (NYSE: CRM) and ServiceNow (NYSE: NOW) dropped approximately 6% on that day, while Microsoft (NASDAQ: MSFT) fell about 3%. The primary cause of this decline appears to be growing fears related to artificial intelligence (AI). Specifically, investors are worried that advanced AI agents, capable of autonomously executing complex tasks across a browser or enterprise environment, could undermine the traditional per-seat software licensing models that many software-as-a-service companies depend on.

Big Demand, But Even Bigger Costs

Despite these challenges, there is evidence that enterprise customers are increasingly interested in AI features. For instance, Salesforce’s AI-driven Agentforce platform has seen explosive adoption, with its annual recurring revenue surging 169% year over year in fiscal Q4 to $800 million. Similarly, ServiceNow has experienced similar momentum, with its Now Assist net new annual contract value more than doubling year over year in its most recent quarter.

ServiceNow’s strong product adoption is also contributing to a healthy backlog of contracted future revenue. Its current remaining performance obligations, which represent contract revenue expected to be recognized over the next 12 months, reached $12.85 billion in Q4 — a 25% increase from the previous year. This growth outpaces the company’s fourth-quarter revenue growth rate of 20.5%.

Microsoft CEO Satya Nadella noted during the company’s most recent earnings call that daily users of Microsoft 365 Copilot were 10 times higher than in the year-ago quarter.

The Catch: Small Revenue Proportions and High Costs

However, despite these impressive numbers, these agentic features still constitute a small portion of overall revenue for these large corporations. Moreover, the infrastructure required to support these features is incredibly expensive.

During this transitional phase, when demand for AI features is high, the costs of delivering these advanced AI features could rise faster than the incremental revenue they generate. Consider Meta Platforms’ changing growth profile. While its fourth-quarter revenue increased by 24% year over year, its earnings per share only rose by 11% due to a narrowing operating margin. This highlights the challenges of scaling in an AI-first era, even for a global company like Meta.

The Integration Curve

Another factor that could exacerbate margin pressure is the customer reality on the ground. Users and organizations may face a prolonged learning, integration, and implementation curve when deploying autonomous agents. While the concept sounds appealing in marketing pitches, practical implementation across thousands of employees requires extensive training, rigid governance, and careful data orchestration.

Additionally, AI is still in its early stages and may not be as capable as some investors hope. When agentic systems are deployed at scale, they may cause more issues and headaches than anticipated, potentially slowing down the sales cycle for premium AI add-ons.

A Difficult Market to Navigate

While some software-as-a-service stocks may benefit from this platform shift, identifying the winners among the wreckage today may not be easy. Companies that successfully integrate these agents at scale and do so profitably will likely see accelerated growth, generating value exceeding their new AI costs.

For most software stocks, the best move right now might be to stay on the sidelines and wait for clear evidence that these software giants can monetize their AI agents faster than they spend to support them.

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